We constructed standardized chronologies of tree-ring width of Larix gmelinii and Pinus sylvestris var. mongolica, the main tree species in the Mangui region of the northern Greater Khingan Mountains based on dendrochronology methods, we explored the responses of radial growth of the two species to climate change. The results showed that the radial growth of L. gmelinii was mainly limited by temperature, which was significantly negatively related to mean temperature in October of the last year and that in March and May-August of the present year. The radial growth of P. sylvestris var. mongolica was promoted by both temperature and precipitation, which was significantly positively related to precipitation in May of the present year and temperature in October of the last year and May-September of the present year. We analyzed temperature data from 1960 to 2021 in the Mangui region using the Mann-Kendall test, and found that mean annual temperature of the region had a warming abrupt change in 1988. L. gmelinii radial growth showed a decreasing trend both before and after the abrupt temperature change, and the downward trend of its radial growth increased slightly after the abrupt change. Radial growth of P. sylvestris var. mongolica changed significantly, with a decreasing trend before the abrupt change and a significant increasing trend after the abrupt change. The response to temperature was enhanced after the abrupt change, with a remarkable positive relationship with the monthly average minimum temperature in May of the present year. The analysis of sliding relationship showed that the sensitivity of L. gmelinii radial growth to climatic factors changed first to increase and then to weaken, and that of P. sylvestris var. mongolica radial growth gradually increased.

We explored the differences in the impacts of drought events on Pinus sylvestris var. mongolica of different ages (30 and 40 years) and different diameter classes (large 20-24.9 cm, medium 15-19.9 cm, small 10-14.9 cm) in the Saihanba Nature Reserve. Based on the tree ring width index (RWI), we analyzed the correlation between radial growth and climatic factors and their ecological resilience to drought events. The results showed that the RWI of 30-year-old small-diameter trees was significantly positively correlated with standardized precipitation evapotranspiration index (SPEI) from September to December of the previous year and February of the current year. RWI of 30-year-old large-diameter and medium-diameter trees was correlated with SPEI from September of the previous year to June of the current year, but the correlation was statistically non-significant. The RWI of 40-year-old large-diameter trees was significantly negatively correlated with the maximum mean temperature in October of the previous year and June of the current year, as well as the mean temperature in June of the current year. The RWI of 40-year-old medium-diameter trees was significantly negatively correlated with the maximum mean temperature and mean temperature in October of the previous year and significantly positively correlated with SPEI in July of the current year. The RWI of 40-year-old small-diameter trees was significantly positively correlated with SPEI from September of the previous year to June of the current year. The resistance of radial growth of trees with different ages to four drought events (40 years old significantly higher than 30 years old) and the resilience exhibited a significant downward trend, while the recovery showed a significant upward trend (40 years old significantly lower than 30 years old). Within the same age group, the responses of P. sylvestris var. mongolica with different diameter classes to drought events were different. The resistance and resilience of large and medium diameter classes of 40-year-old trees were significantly higher than those of small diameter class trees, but their recovery showed no significant difference. For 30-year-old trees, there were no significant differences in resistance, recovery, or resilience among different diameter classes. P. sylvestris var. mongolica of different ages and diameter classes experienced varying degrees of drought stress, resulting in a significant decrease in resilience. The 40-year-old trees exhibited high resistance, while the 30-year-old trees showed high recovery capability. Small diameter class trees were most severely affected by drought stress.

Tree heart rot is widespread in forests, which could affect forest health and bring uncertainties in the estimation of forest carbon sequestration. However, the impacts of heart rot on radial growth of trees are not well understood. Tree-ring data from heart-rotted and healthy trees of Abies georgei var. smithii at altitudes of 3700 m (low-altitude), 4000 m (mid-altitude), and 4300 m (high-altitude) in the Sygera Mountain region of southeastern Xizang were used to compare radial growth and its relationship with climatic factors. The results showed that the positive effect of rapid warming on the radial growth of heart-rotted A. georgei var. smithii in mid- and high-altitude regions was lower than that of healthy trees, while the negative effect on the growth of low-altitude heart-rotted trees was higher than that on healthy trees. In both periods before and after warming, the radial growth rates of heart-rotted trees at all three altitudes were significantly lower than those of healthy ones. With the occurrence of heart rot, the effect of temperature on the radial growth of low-altitude A. georgei var. smithii shifted from promotion to some degree of inhibition. The sensitivity of heart-rotted trees in mid-altitude regions to temperature factors during the previous year’s growing season was lower than that of healthy trees, while the sensitivity of heart-rotted trees in the treeline area to temperature was only slightly different from that of healthy trees. Under the background of future climate warming, warming would promote the radial growth of A. georgei var. smithii in the region, and exacerbate the differences in growth rates between heart-rotted and healthy trees.

Understanding how plants respond to drought and re-irrigation is crucial for the successful breeding of seedlings in artificial forests in semi-arid regions of China, as the frequency of high-intensity drought events has significantly increased in these areas. We conducted an experiment with four drought stress treatments, including no reduction in rainfall (control), 25% reduction in rainfall (mild stress), 50% reduction in rainfall (moderate stress), and 75% reduction in rainfall (severe stress). We subjected two-year-old Pinus tabuliformis seedlings to a long-term drought stress period of 20 months, followed by a high-intensity drought treatment (continuous 80 days with 100% rainfall reduction). Additionally, we administered re-irrigation treatments lasting 10 days on days 10, 40, 70, and 80 of the high-intensity drought period. We aimed to investigate the relationships among hydraulic conductivity, percentage loss of hydraulic conductivity, and the content of osmotic adjustment substances in new branches of P. tabuliformis, as well as their responses to drought. The results showed that under long-term drought stress, the water potential threshold at which hydraulic conductivity loss reached 50% for new branches under mild stress was -2.04 MPa, which was significantly lower than that of the other treatments. After 80 days of high-intensity drought, the proline content in new branches increased significantly by 19.9% to 226.0% compared to the initial value. Redundancy analysis showed that proline explained 40.4% of the variability in hydraulic function and was the primary osmotic adjustment substance during high-intensity drought. During re-irrigation, soluble sugars explained 29.4% of the variability in hydraulic function and were the main osmotic adjustment substances in this stage. Different factors accounted for the differences in hydraulic function of P. tabuliformis during drought and re-irrigation. Mild stress enhanced the embolism resistance under the long-term drought. New branches of P. tabuliformis maintained normal water transport by accumulating proline in response to high-intensity drought. During re-irrigation, soluble sugars were significantly positively correlated with hydraulic conductivity, which facilitated embolism repair and enhanced the recovery of hydraulic function.

To understand the changes and relationship of plant-soil eco-stoichiometric characteristics of Pinus tabuliformis plantations with stand ages, we investigated P. tabuliformis plantations of different stand ages (10, 23, 39, and 47 years old) in the Taihang Mountains. We measured the concentration and stoichiometry of carbon (C), nitrogen (N), and phosphorus (P) in leaves, branches, and soils at different layers. We analyzed the relationship between leaf, branch nutrient characteristics and soil physicochemical properties. The results showed that soil C and N contents decreased after an initial increase with increasing stand ages, being the maximum at the 39 years old stand, while P content was the maximum at 47 years old stand. Soil C:P and N:P of the 23 years old stand were significantly higher than that of other stand ages, indicating that P was the limiting factor for P. tabuliformis growth. With increasing soil depth, the concentration of C, N, P, C:P and N:P in soils of different stand ages decreased, while the C:N increased, suggesting an enhanced N limitation. The stoichiometric characteristics of soils at different depths varied significantly among different stand ages, particularly in the upper soil layers (0-20 cm). The N content in leaves and branches increased first and then decreased, while the P content decreased first and then increased. The C:P and N:P in leaves and branches were higher at 23 years old, indicating a synergistic effect of nutrient acquisition between leaves and branches. Soil C concentration was significantly positively correlated with leaf N, while soil C:N was significantly positively correlated with branch C:N. There was a stronger correlation in the deeper soil layers (20-60 cm) than the upper soil layers. Soil sand content and N:P were key factors influencing nutrients in leaves, while soil P and C contents were the main factors influencing nutrients in branches. Soil water content (SWC), soil N content, and soil C:N jointly regulated nutrient variations in leaves and branches. Compared to the upper soil layers, the deeper soil layers showed a more pronounced N limitation. The impact of SWC on nutrient availability was relatively minor. Soil C:N (17.0) was higher than the national average, while the N:P in both leaves (8.2) and branches (8.3) were lower than 14, indicating increasing N limitation with increa-sing stand ages. To ensure the development of P. tabuliformis plantations and improve nutrient cycling, P and N fertilizers could be applied during the mid to late growth stages of P. tabuliformis plantations.

To elucidate the regulatory effects of decaying coarse woody debris on soil carbon and nutrient balance, we measured soil organic carbon, nitrogen, and phosphorus contents and stoichiometric ratios in the topsoil (0-10 cm) beneath Minjiang fir (Abies faxoniana) coarse woody debris of decay classes Ⅰ-Ⅴ, with diameter of 10-30 cm and 30-50 cm in a subalpine coniferous forest. Areas without coarse woody debris situated at least 1 m away from the debris were set as control. The results showed that decaying coarse woody debris significantly increased contents of soil organic carbon (114.1%-412.2%) and nitrogen (0.1%-198.0%), as well as C/N (61.7%-117.1%), C/P (379.6%-931.1%) and N/P (206.3%-532.6%) in soils, but significantly udecreased soil phosphorus content by 28.1%-70.9%. The effects of coarse woody debris on soil organic carbon, nitrogen, and phosphorus content varied with decay classes and diameters. The content of organic carbon and nitrogen in soils beneath large diameter coarse woody debris at decay classes Ⅲ and Ⅳ were significantly higher than those beneath coarse woody debris with small diameter. Soil phosphorus content beneath large diameter coarse woody debris at decay class Ⅲ was significantly higher than that beneath small diameter. Moreover, ecological stoichiometric ratios in soils beneath large diameter coarse woody debris exhibited significant correlations with organic carbon, nitrogen, and phosphorus content of coarse woody debris. In conclusion, retaining larger diameter coarse woody debris with medium to highly decayed classes on the forest floor is beneficial for soil nutrient balance.

Soil organic carbon turnover and stabilization are closely related to nitrogen deposition and litter decomposition. However, there are great uncertainties about how the decomposition of bamboo litter driven by nitrogen deposition affects soil organic carbon components. To investigate the effects of nitrogen deposition-driven litter decomposition on soil organic carbon components, we conducted an experiment at the Anji Moso bamboo ecosystem research station of Zhejiang A&F University with nitrogen treatments (N, 50 kg N·hm^-2·a^-1; CK, control with equal amount of water) and litter treatments (L, litter retention; LR, litter removal) to analyze changes in litter mass loss, soil physicochemical properties, particulate organic carbon (POC), mineral-associated organic carbon (MAOC), and soil extracellular enzyme activity (EEAs). The results showed that nitrogen application significantly reduced the mass loss of leaf litter. Nitrogen application significantly increased POC content and decreased MAOC content, but litter retention significantly increased the contents of POC and MAOC in soil. Nitrogen application significantly decreased the activities of β-1,4-glucosidase (BG), β-1,4-xylosidase (BX), cellobiohydrolase (CBH), β-1,4-N-acetyl-glucosaminnidase (NAG), phenol oxidase (POX), and peroxidase (PER), while litter retention significantly increased the activities of BG, POX, and PER. Results of correlation analysis and random forest analysis showed that the key factors affecting the decomposition of Moso bamboo litter under nitrogen treatment were BG, PER, pH, microbial biomass carbon (MBC) and POX. Through redundancy analysis (RDA) and regression fitting analysis, we found that POC was significantly negatively correlated with mass loss, MBC, BG, CBH, POX and PER, and significantly positively correlated with ammonium nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃^--N). MAOC was significantly positively correlated with mass loss, pH, MBC, CBH, NAG, POX and PER, and negatively correlated with microbial biomass nitrogen (MBN). In conclusion, nitrogen deposition inhibits bamboo leaf litter decomposition by reducing extracellular enzyme activities, thereby increasing soil POC content and decreasing MAOC content.

Exploring the spatiotemporal variations and response characteristics of global vegetation and extreme climate is of great significance for addressing global climate change and improving ecosystem stability. Based on ERA5 climate data from the European Centre for Medium-Range Weather Forecasts and MODIS normalized difference vegetation index (NDVI) data, we used Sen’s trend analysis, correlation analysis, and random forest regression model to explore the responses of NDVI of five vegetation types (boreal and temperate forest, tropical forest, other woody vegetation, grassland, and cropland) to 23 extreme climate indices from 2001 to 2020. The results showed that global NDVI showed an overall increasing trend from 2001 to 2020. The areas with the most significant growth trend was boreal and temperate forest, and the least significant growth trend occurred in cropland. In terms of extreme climate index, except for a few extreme high temperature and low temperature indices, the other indices showed an increasing trend. Across different vegetation areas, the extreme climate index that had the greatest influence on NDVI was different. The results of correlation analysis showed that the indices with the greatest impact on NDVI in the boreal and temperate forest, tropical forest, other woody vegetation, grassland, and cropland were cold days, ice days, annual total precipitation, annual total precipitation, and annual total precipitation, respectively. The results of random forest analysis showed that the indices with the greatest impact on NDVI in each vegetation zone were cold days, warm night days, frost days, warm days, and the cold spell duration index, respectively. The reason for the different results between the two methods was that correlation analysis only reflected linear relationships between variables, while the random forest regression model could capture more complex nonlinear relationships. Our results showed that the response of global vegetation to extreme climate had significant regional differences and complexities, which may result from interactions between different climate factors.

Environmental and genetic differentiation jointly influence intra-specific variations of plant functional traits. Research on this topic is of great importance for the assessment plant adaptation to climate change and for developing long-term conservation strategies. In a common garden experiment, we investigated the variations in root and leaf functional traits of Caragana jubata across 14 provenances, as well as their relationships with the climatic and geographic factors of seed origin. The results showed that there were significant intraspecific differences in leaf tissue density, specific leaf area, leaf length to width ratio, leaf shape factor, leaf chlorophyll content, leaf nitrogen concentration, as well as root average diameter, specific root length, specific root area, and root nitrogen concentration. Leaf tissue density and root nitrogen concentration were key indicators explaining the differentiation of leaf and root functional traits across the various provenances. There were significant trade-offs among leaf and root functional traits, as indicated by the significant negative correlation between leaf area and leaf tissue density, between specific root length and root tissue density, as well as between leaf nitrogen concentration and root nitrogen concentration. Mean annual precipitation, growing season precipitation, altitude and geographical factors (longitude and latitude) of the seed origin played crucial roles in influencing intraspecific variation of leaf functional traits, while altitude dominantly accounted for the intraspecific variation of root functional traits.

To investigate the adaptability of annual herbaceous species in deserts, we collected root samples of four common annual herbaceous plants in the sand-fixing vegetation area on the southeastern edge of the Tengger Desert, namely Agriophyllum squarrosum, Stilpnolepis centiflora, Corispermum hyssopifolium, and Grubovia dasyphylla, through the traditional excavation approach. Based on the quantification of root morphology indicators, we analyzed root characteristics using geometric topology and fractal theory, and compared the diversity of root characteristics and the differences in adaptation mechanisms among the four species. The results showed that root-shoot ratio and root depth-width ratio of the four species followed an order of A. squarrosum > S. centiflora > C. hyssopifolium > G. dasyphylla. The specific root length and specific surface area followed an order of A. squarrosum < S. centiflora < C. hyssopifolium < G. dasyphylla. The root topology index TI and the modified topology indices q_a and q_b exhibited the same trend, with an order of A. squarrosum > S. centiflora > C. hyssopifolium > G. dasyphylla. The root fractal dimensions of A. squarrosum, S. centiflora, C. hyssopifolium, and G. dasyphylla were 1.215, 1.278, 1.387 and 1.631, and the root fractal abundances were 3.528, 3.248, 2.479 and 2.451, respectively. A. squarrosum and S. centiflora adopted a high growth resource strategy, featuring simple root structure, tending towards the fish-tail-shaped branching structure, and possessing strong abilities of vertical resource acquisition and spatial expansion, while C. hyssopifolium and G. dasyphylla adopted a high-quality resource strategy, having more complex root structure, with forked branching and higher resource utilization efficiency.

Gymnadenia conopsea is an endangered medicinal plant. Due to climate change and human activities, as well as the low reproductive capacity, the wild resources of G. conopsea are extremely scarce and it has been listed in the Chinese National Second Level Protected Plant List. Predicting the potential suitable distribution area of G. conopsea is crucial for the conservation and sustainable utilization. With climate and soil data from 118 distribution points, we used MaxEnt model combined with ArcGIS technology to predict the suitable distribution area of G. conopsea in China under future climate change. The results showed that the area value (ACU) under the receiver operating characteristic curve (ROC) was 0.808, indicating good prediction performance. The main environmental factors affecting the distribution of G. conopsea were mean temperature of the warmest quarter, seasonal precipita-tion, soil factors such as the subsoil sodicity (30-100 cm), topsoil gravel (0-30 cm), subsoil cation exchange capacity (30-100 cm), annual precipitation and precipitation of the driest month. At present, the potential total suitable distribution area of G. conopsea in China was about 50.22×10⁵ km², concentrated in north, northeast and southwest China, including Inner Mongolia, Heilongjiang, Jilin, Liaoning, Sichuan, Shanxi and Southeast Xizang. Under future climate scenarios, the suitable habitat range would shrink, and migrate to higher altitude regions such as Xizang, Yunnan, and Sichuan, indicating that global warming may pose a threat. This result could provide scientific basis for the ecological protection, resource development, and sustainable utilization strategies of G. conopsea germplasm resources.

Farmland ecosystems are strongly affected by climate change, but the effects of global warming and precipitation changes and their interactions on soil organic carbon and enzyme activities in farmland soils and their relationships are still poorly understood. In this study, we employed the Open-Top Chamber (OTC) warming platform and the precipitation manipulative platform to investigate the effects of warming and precipitation changes on soil organic carbon and enzyme activities in semi-arid spring wheat farmland in Loess Plateau of the central Gansu Pro-vince. There were six treatments: control (CK), 30% precipitation reduction (-P₃₀), 30% precipitation increase (+P₃₀), warming (W), warming and 30% precipitation reduction (W-P₃₀), and warming and 30% precipitation increase (W+P₃₀). The results showed that OTC warming significantly elevated soil organic carbon (SOC), microbial biomass carbon (MBC), readily oxidizable organic carbon (KMnO₄-C), dissolved organic carbon (DOC), and particulate organic carbon (POC) contents. In contrast, the mineral associated organic carbon (MAOC) content changed little. Under ambient temperature, neither an increase nor a decrease in precipitation resulted in a significant alteration of soil organic carbon fractions. However, under the warming condition, elevated precipitation resulted in a notable enhancement in DOC and POC contents. Warming and precipitation significantly interacted to affect SOC, DOC, and KMnO₄-C contents. The interaction between precipitation and warming resulted in an increase in the carbon pool management index (CMI), the carbon pool index (CPI), the activity of soil cellobiose hydrolase, urease, sucrase, N-acetyl-β-D-glucosidase, as well as crop biomass. The correlations between soil temperature, moisture, soil organic carbon fractions and enzyme activities were positive. There was a negative correlation between soil temperature and sucrase activity. The random forest modelling analysis demonstrated that soil physicochemical properties, enzyme activities, temperature and water content together explained 52.4% to 71.1%, and the five factors with higher correlation importance were soil urease activity, soil temperature, soil moisture, soil N-acetyl-β-D-glucosidase activity, and effective phosphorus. However, the selected factors only accounted for 21.5% of the observed variation in MAOC content. In conclusion, warming and precipitation changes significantly affected soil properties, enzyme activities and crop biomass, and thus soil organic carbon pools, in semi-arid wheatland soil of Loess Plateau of central Gansu Province.

This study aimed to clarify the impacts of elevating CO₂ concentration (e[CO₂]) on maize “source-sink” characteristics in maize intercropping with peanut system. We investigated the impacts of e[CO₂] on leaf “source” quantity, gas exchange parameters, population “source” productivity, “sink” capacity, grain to leaf ratio, yield and intercropping advantage of maize under 0 (P₀) and 180 kg P₂O₅·hm^-2(P₁₈₀). The results showed that compared with ambient CO₂ concentration (a[CO₂]), e[CO₂] augmented leaf “source” quantity and “source” activity of intercropping maize, and significantly increased productivity of population “source”. The silk maximum number, actual seed number and effective “sink” capacity were increased by 8.0%-9.3%, 10.0%-13.4%, and 10.4%-20.8%, respectively. Concurrently, the average dry matter accumulation rate of grains was significantly increased by 10.7%-50.4%. The grain to leaf ratio and harvest index were increased by 3.3%-7.4% and 2.4%-7.9%, respectively. The yield and intercropping advantage were increased by 10.8%-48.7% and 20.4%-102.7%, respectively. Under e[CO₂], phosphorus application could further improve the “source-sink” relationship and maize yield, and increase the intercropping advantage. In summary, e[CO₂] enhanced the “source” performance and “sink” capacity of intercropping maize, promoted grain filling, regulated the “source-sink” relationship, enhanced yield, and thus increased the intercropping advantage.

Soil conditioners are efficacy in ameliorating saline-alkali soils and fostering crop growth. To explore the effect and physiological mechanism of soil conditioner on improving the adaptability of maize to saline-alkali stress, we conducted a field randomized block experiment in Liuzhong Village, Pingluo County, Ningxia Province in 2022. We investigated the variations of antioxidant capacity, key enzyme activities and photosynthetic fluorescence properties of maize induced by soil conditioners under saline-alkali stress, with “Xianyu 1255” maize as the experimental material under four treatments: T₀(no conditioner, control), T₁(humic acid), T₂(microsilica fume + wood vine-gar solution), T₃(humic acid + wood vinegar solution + microsilica fume). The results showed that soil conditioner could enhance the antioxidant capacity, key enzyme activity and photosynthetic fluorescence characteristics of maize leaves. The superoxide anion scavenging rate and superoxide dismutase activity of each treatment in the two growth stages (jointing stage-big flare stage and grain filling stage) were significantly increased and the content of malon-dialdehyde was significantly decreased. The aquaporin activity of each treatment in the jointing stage-big flare stage was significantly enhanced. Transpiration rate, net photosynthetic rate, stomatal conductance, non-photochemical quenching coefficient, apparent synthetic electron transfer rate and actual photochemical efficiency were significantly enhanced, while the intercellular carbon dioxide concentration was significantly decreased in T₂ and T₃ treatments. The hydroxyl radical scavenging rate and initial fluorescence of each treatment were significantly increased in each treatment at the grain filling stage. T₃ performed the best. Structural equation modeling and membership function analysis confirmed that soil conditioners could bolster the antioxidant system and aquaporin activity in maize, mitigate membrane lipid peroxidation, enhance stomatal conductance, and improve photosynthesis, thereby improve the resistance of maize to saline-alkali. The combined application of humic acid, wood vinegar, and microsilica fume was the most effective one.

We investigated the effect of single seed directional sowing on the growth and development of peanut hypocotyl, plant photosynthetic performance, dry matter accumulation, senescence characteristics and yield of a peanut variety, Huayu 25. There are several treatments in the experiment, including single-seed random sowing (RS), radicle down (RD), radicle flat (RF) and radicle up (RU) treatments, with double seed sowing cleaning stem base soil (QK) as the control. The results showed that under the condition of single seed directional sowing, RD could increase the growth rate of peanut hypocotyl, shorten the emergence time, increase the emergence rate and cotyledon emergence rate, and had faster plant growth rate, higher leaf area index in the early stage of peanut growth, and an increased dry matter accumulation. The pod yield under RD was 8.1%, 14.4%, and 18.1% higher than that of RF, RS, and RU, respectively. Furthermore, RD significantly increased soluble protein content and the activities of superoxide dismutase, peroxidase and catalase, and reduced malondialdehyde (MDA) accumulation. Compared with QK, the soluble protein content, superoxide dismutase, peroxidase and catalase activities of RD in different periods were increased to varying degrees, while the MDA content was decreased, and there was no significant difference in pod yield. Our results suggested that RD could reduce the emergence time and the competition between plants, promote the growth of seedlings, accelerate the formation of seedling morphology, so as to establish a reasonable population structure, enhance the photosynthetic efficiency and dry matter production capacity of the population, effectively delay the aging process of the crop in the later stage, and finally increase pod yield.

Soil salinization and alkalization is a serious constraint to sustainable development of agriculture. Timely acquisition of soil salinity content (SSC) and pH information is crucial for improvement and rational utilization of saline-alkaline farmlands. We collected the data of field hyperspectral information and salt and alkali indicators in the surface layer (0-20 cm) and sub-surface layer (20-40 cm) in Pingluo County, Shizuishan City from Ningxia. We transformed the original spectral reflectance by Savitzky-Golay (SG) smoothing with the fractional order differentiation (FOD) of order 0-2 (with an interval of 0.25), constructed nine spectral indices, and established the inverse models of SSC and pH based on three machine learning algorithms, namely partial least squares regression (PLSR), random forest (RF) and extreme random tree (ERT), after the screening of feature covariates according to the correlation between the indices and the examined salt and alkali indicators. The results showed that 1) the spectral reflectance of the surface layer was always multiplicative with the subsurface layer, and the FOD transform could effectively eliminate the baseline drift of the spectral curves, highlighting the subtle spectral information. 2) Both surface and subsurface SSC were most strongly correlated with the difference index (DI), the optimal spectral index (OSI), and the soil-adjusted spectral index (SASI), with optimal transformation orders of 1.5 and 0.75, respectively. For pH, the strongest correlations were with the ratio index (RI), the generalized index (GDI), and the normalized index (NDI), with optimal orders of 0.5 and 0.25, respectively. 3) The ERT model performed the best with respect to the salt and alkali indicators of different soil layers. The accuracy of SSC inversion was higher in the surface layer than in the subsurface layer, while the opposite was true for pH. The coefficient of determination for the validation set (R_p²), root mean square error (RMSE), and relative predictive deviation (RPD) for the surface SSC-1.5 order-ERT model were 0.980, 0.547, and 5.229, whereas the R_p², RMSE, and RPD of the subsurface pH-0.25 order-ERT model were 0.958, 0.111, and 4.685, respectively. Those values indicated high accuracy of the models. This study would provide technical support for the rapid acquisition and inversion mapping of farmland salinity and alkalinity information.

Soil salinization is a common factor constraining agricultural production safety, achieving rapid and accurate acquisition of cultivated land soil salinity information is of paramount importance for ameliorating and resolving soil salinization problems. In this study, with unmanned aerial vehicle (UAV) hyperspectral remote sensing data as the data source, we selected feature band subsets using various spectral transformation data based on different land use statuses of cultivated land, to compare the model accuracies of Support Vector Machine (SVR), Back Propagation Neural Network (BPNN) and Random Forest regression (RFR), and propose the optimal inversion model for regional cultivated land soil salinity. The results showed that the inversion model combining first-order differential spectral transformation data with RFR achieved the highest accuracy. Extracting feature bands separately for cultivated land with different land use statuses would ensure a higher overall model accuracy, with a coefficient of determination of 0.885, a root mean square error of 0.413, and a ratio of performance to deviation of 4.208. Our results could provide a reference for achieving high-precision inversion of soil salinity in cultivated land by UAV hyperspectral technology, and offer scientific support for the prevention and control of soil salinization in cultivated land.

Due to natural factors and influences from neighboring countries, wild fires frequently occur in China’s border areas. To quantify the activities of wild fires in border areas, we analyzed the regime of wild fires within a 2 km buffer zone on both sides of China’s land borders based on MODIS fire spot data, including fire types, fre-quency, seasonality, and spatial distribution. Between 2001 and 2022, a total of 25918 vegetation fires occurred in China’s border regions, with forests, cropland, and grasslands accounting for 42.0%, 30.4%, and 14.4% of the fire incidents, respectively. Forest fires were most common in broadleaved forests. Cropland fires mainly resulted from traditional farming practices and the lack of fire prevention awareness among border residents, which often caused fires to spread to nearby forests, leading to forest fires. Among grassland fires, meadow steppe posed the highest risk, and grassland fires in forest-grassland ecotones were likely to trigger forest fires. There were significant differences in fire types and seasonal distribution across regions. In the northeastern border region, grassland fires, deciduous broadleaved forest fires, and cropland fires were predominant, with spring and autumn being the primary seasons for fire occurrences, especially in April and October. In the southwestern border region, evergreen broadleaved forest fires and cropland fires were predominant, with spring and winter being peak periods for fires, especially in March and December. In the northwestern border region, grassland fires and cropland fires were predominant, with more vegetation fires occurring in summer and autumn, peaking in September. Within a 2 km range on both sides of the border, the number of fire spots outside the country far exceeded those within, particularly in the border areas of Inner Mongolia, Jilin, Yunnan, and Guangxi, increasing the risk of cross-border fires in these regions. Fire spots showed significant clustering, with major clusters found in the border region of Xishuangbanna Dai Autonomous Prefecture in Yunnan, Hulunbuir City in Inner Mongolia, Huma County and Jiamusi City in Heilongjiang, and Hunchun City in Jilin. Different fire prevention strategies should be developed based on the characteristics of vegetation fires in different border regions, targeting vegetation types, seasonal periods, and clustering areas prone to fires, to implement effective vegetation fire prevention and control measures in border areas.

Solar-induced chlorophyll fluorescence (SIF) has been widely used in different area, such as estimating forest gross primary productivity (GPP), monitoring drought, estimating evapotranspiration and tracking vegetation phenology. Based on the Global OCO-2 SIF product (GOSIF) and the standardized precipitation evapotranspiration index (SPEI) at different temporal scales (1, 3, 6, and 12 months), we explored the responses of forest photosynthesis to dry-wet change over eastern monsoon China during 2001-2021. The results showed that there were differences in drought intensity and frequency among forests in different geographical regions. Forests in the North China and East China experienced higher drought intensity, while the southern part of Northwest China had lower drought intensity. Forests in the North China experienced more frequent droughts, while the Northeast China and Southwest China had lower drought frequencies. About 74.1% of the area where forest GOSIF was significantly and positively correlated with SPEI, and the response of photosynthesis to SPEI showed the most pronounced at the 1-month scale. In different geographical regions, photosynthesis in the Northeast China was the most sensitive to SPEI, whereas in the North China it was the least sensitive. The drought resistance of forests in the southern part of Northwest China exhibited the strongest, while in the Northeast China it was the weakest. Meanwhile, in different forest types, deciduous broad-leaved forests were the most sensitive to SPEI, followed by mixed forests, evergreen broad-leaved forests, evergreen needle-leaved forests and deciduous needle-leaved forests. Evergreen needle-leaved forests had the strongest resistance to drought stress, followed by deciduous needle-leaved forests, evergreen broad-leaved forests, deciduous broad-leaved forests and mixed forests. During the growing season (May-September), the response sensitivity of photosynthesis to SPEI was strongest in June and weakest in July. Dry-wet changes at the 1 and 3-month scales exerted the main impact on photosynthesis, while in the mid-season (June-August) and late season (September), the impact of dry-wet changes at the 6 and 12-month scales on photosynthesis increased.

Understanding the coordinated transformation of green ecological-living-production space is an important task for 26 mountainous counties of Zhejiang Province to achieve leapfrog high-quality development. Following the framework of ecological-living-production space, we analyzed the dynamics and driving factors of the coupling transformation of the ecological-living-production system in 26 mountainous counties from 2010 to 2021, based on coupling coordination model, kernel density estimation, spatial Markov chain model and optimal parameter geodetector model. The results showed that, the coupling coordination degree of the green transformation of the ecological-living-production system had significantly increased, and the gap among counties had shown an evolutionary trend of stepwise narrowing. In 2016, there was a polarization phenomenon. The coupling coordination degree of the green transformation of the ecological-living-production system presented a spatial pattern of “high in the east and low in the west, high in the north and low in the south”. The spatial directivity characteristics were gradually obvious, while the spatial structure evolution showed the characteristics of collaborative response. There was an obvious “club convergence” phenomenon in the coordinated transformation of the ecological-living-production, and each convergence club had strong stability. It was difficult for the coupling coordination type to achieve leap-forward transfer in adjacent years, and there were still “path dependence” and self-enhancement “lock-in effect”. The spatial lag factor had a greater influence on the type of coupling coordination. The counties with higher coupling coordination degree had a greater probability of driving the neighboring counties to move upward, whereas the counties with low coupling coordination degree may inhibit the improvement of the coupling coordination degree of the surrounding counties. The coordinated transformation of the ecological-living-production system in 2010, 2015, and 2021 was driven by the progress of social civilization, opening up and economic development, economic development and scientific and technological development, respectively. Our results had important supporting value for the green transformation of collaborative regional ecological, living, and production spaces.

Mountainous and hilly regions are one of the mainstays of national ecological security barriers. To avoid the impact of terrain undulations on the ecological environment quality assessment, we used the normalized difference mountain vegetation index (NDMVI) as the greenness ecological factor, combined with the humidity, aridity, and thermal factors, to construct the improved the hilly remote sensing ecological index (HRSEI) for mountainous areas based on the remote sensing ecological index (RSEI). We assessed ecological quality in two typical mountai-nous and hilly areas, i.e., Changting County in Longyan City, Fujian Province, and Shanyang County in Shangluo City, Shaanxi Province. We compared the ecological quality grade transition paths of HRSEI and RSEI, and verified the applicability of HRSEI in mountainous areas. The results showed that NDMVI could extract more vegetation information in mountainous areas than NDVI. The greater the topographic relief, the stronger the ability of NDMVI to extract vegetation information. Verified through average correlation and stepwise regression equations, HRSEI was representative for the ecological quality assessment of mountainous and hilly areas. HRSEI mainly upgraded the vegetation ecological grade from good to excellent for some areas affected by shadows. Compared with the extraction results of RSEI, areas classified as excellent increased by 13.75 and 41.88 km² in Changting and Shangyang, respectively. Combined with high-resolution imagery, the areas with improved ecological quality corresponded to high-vegetation-cover areas affected by mountain shadows, indicating that HRSEI could effectively improve the identification accuracy of high-vegetation-cover areas influenced by shadows, making it more practical.

Inland lakes are important surface water resources in arid Central Asia. Due to the superimposed influence of natural factors and human factors, the hydrological characteristics of arid lakes show significant temporal and spatial variations. However, data shortage in this area makes it difficult to carry out detailed and long-term quantitative monitoring of hydrological regimes for different lakes. Based on the Google Earth Engine Platform (GEE), we firstly selected the Landsat 5/7/8 remote sensing image data that completely covered the Saram Lake and Ebinur Lake during 1990-2021, and used the multi-remote sensing index decision tree method to extract the continuous long time series of lake area. Combined with lake water level extracted by CryoSat-2 and ICESat-2 alti-meter satellites, we constructed the storage capacity curve based on the relationship between lake area and water level, and estimated the water volume change information of the lakes. Finally, combined with the hydrological, climate and population factors data of the basin, the correlation analysis and random forest method were used to quantitatively compare and analyze the factors of water quantity variation between the two lakes. The results showed that both Saram Lake and Ebinur Lake had expanded during 1990-2021, though with quite different water conditions. The area of Saram Lake increased by only 1.3%, with little interannual variation. The water volume increased by 1.12 km³ at a growth rate of around 0.04 km³·a^-1. Conversely, the area of Ebinur Lake experienced a 30.1% expansion and exhibited significant annual fluctuation, averaging approximately 0.01 km³·a^-1. Annual precipitation and glacial meltwater were the main factors affecting the water content of the Saram Lake, with contribution rates of 33% and 27%, respectively. However, temperature and precipitation were the main factors affecting the water quantity change of Ebinur Lake, and their contribution rates in the process of water quantity change were both 28%. The aim of this study was to use remote sensing technology to reveal the characteristics of lakes’ dynamic change and the difference of its response to their external environment in arid areas with the shortage of measured data, which would provide scientific reference for lake ecological environment and water resources protection in arid areas.

Water resources are essential for sustaining life, driving economic development, and protecting the environment. We investigated the hydrochemical variations of surface water and groundwater in the Shandian River Basin to identify the driving factors and the transformation relationship between each water body. Precipitation data was collected from May to October 2023, while surface water and groundwater samples were collected in both August (wet season) and October (dry season). We analyzed water samples by Piper triplex diagram, Gibbs diagram, ion ratio method, hydrogen and oxygen isotope analysis, and MixSIAR mixed model. The results indicated that both groundwater and surface water were generally weakly alkaline. The dominant type of groundwater chemical composition was HCO₃^--Ca²⁺·Na⁺.During the process of surface water transitioning from the wet season to the dry season, the predominant surface water chemistry type shifted from HCO₃^--Ca²⁺-Na⁺ to HCO₃^--Na⁺-Mg²⁺, as well as HCO₃^--Ca²⁺-Na⁺-Mg².Furthermore, the main hydrochemical types of surface water changed during the transition from wet season to dry season. The hydrochemical characteristics of different types of water were influenced by weathering of rocks, evaporation and concentration of water, as well as cation exchange. Additionally, significant enrichment of δD and δ¹⁸O isotopic values in surface water was observed during the wet season, and the ground-water remained in a depleted state during both wet and dry seasons. During the wet and dry seasons, the slope of surface water line was lower than that of the precipitation line, and the slope of groundwater line during the wet season was similar to that of the precipitation line and the surface water line, indicating the complexity of the conversion relationship between various water bodies during the wet season. The precipitation served as ~70% primary recharge source for surface waters, whereas underground aquifers contributed ~30%, being the secondary recharge source. During the dry season, groundwater replenished surface water. These findings would provide fundamental support for effective resource management and protection practices related to the basin.

Macrozoobenthos play a pivotal role in the biogeochemical cycling of C, N, and P in nearshore marine ecosystems by nutrient retention and recycling. To maintain the dynamic equilibrium in elemental contents, zoo-benthos must get a balance with their resource supply or alter their stoichiometric characteristics in response to environmental changes. We investigated the ecological stoichiometric characteristics of six macrozoobenthos species, including bivalve (Moerella jedoensis, Nitidotellina minuta, Mizuhopecten yessoensis) and ophiuroidea (Amphioplus japonicus, Ophiura sarsii vadicola, Ophiopholis mirabilis), which were collected from the coastal waters of Dalian Island in the northern Yellow Sea in May and August 2020. Results showed that the range of C, N, and P contents in the six species was 23.4%-49.8%, 4.3%-14.7%, and 0.1%-1.1%, respectively. The range for C:N, C:P, and N:P was 3.12-6.75, 29.01-410.63, and 6.32-113.9, respectively. The P content exhibited a relatively larger range of variation than C and N, leading to higher variability in C:P and N:P. There were significant differences in element contents and ratios between the two groups, bivalve and ophiuroidea. The stoichiometric characteristics of the three shellfish species under bivalve was significantly different in N content, C:N and N:P, while the three ophiuroidea species had significant differences except for C content, indicating that the ecological stoichiometric characteristics of marine macrozoobenthos had interspecific differences. The ecological stoichiometric characteristics of the same group and species were not significantly different between the two months. There was a significant correlation between the stoichiometric characteristics of macrozoobenthos, except for C content and P content, C content and C:P, N content and C:P.

To effectively distinguish natural and cultured populations of Oplegnathus fasciatus, we used both traditional statistical analysis and neural network methods to compare six shape indices and twenty-one truss indices from otoliths of 174 randomly selected specimens (100 from a natural population and 74 from a cultured population). The results showed that among the six shape indices, ellipticity, roundness, and aspect ratio exhibited significant differences between the two populations. Twelve out of the twenty-one truss indices displayed significant differences. Results of discriminant analysis indicated that traditional statistical analysis and neural network methods achieved correct discrimination rates of 57.5% and 81.4% for shape indices, while for truss indices were 69.5% and 85.4%, respectively. These findings indicated that neural network technique is more effectively than traditional statistical method to distinguish natural and cultured populations of O. fasciatus.

Setipinna taty, a dominant fish species in the southern Zhejiang coastal waters, plays an important role in the coastal marine ecosystem. Based on 847 S. taty samples collected from southern Zhejiang coastal waters between May 2020 to January 2021, we examined prey composition, seasonal and ontogenetic diet variations, as well as their relationships with environmental factors, with stomach content analysis, cluster analysis, and canonical correspondence analysis (CCA). Results showed that S. taty consumed 43 prey species, with shrimp, Amphipoda and krill as the most important prey groups. The dominant prey species were Leptochela gracilis, Oxycephalus clausi, and Euphausia pacifica. There were significant seasonal and ontogenetic variations in the prey composition of S. taty. Shrimp was the dominate prey group in all seasons. S. taty consumed certain amount of fish in summer and a high proportion of Euphausiacea in winter. With the increases of body length, the main prey species gradually shifted from small size prey items such as copepods to larger ones such as fish and shrimp. Results of CCA indicated that salinity and pH were the main factors influencing feeding habit of S. taty, followed by water depth, latitude and body length. This study could provide basic information for the food web study in the southern Zhejiang coastal waters.

As an important component of aquatic ecosystem, fish habitat is crucial for maintaining aquantic ecosystem, species diversity, and sustainable fisheries. To reveal the suitability of habitat factors and distribution patterns of Schizothorax wangchiachii in the Heishui River of the lower Jinsha River tributary, we selected the habitat indicators by the Spearman correlation single tail test, calculated the fish habitat suitability index by the random forest algorithm and weighted average method, based on the fish catch data and 16 related environmental factor data collected from 2018 to 2019. The results showed that the optimal range of water temperature, water depth, and altitude for S. wangchiachii was 16.3-16.8 ℃, 35-60 cm, and 637-816 m, respectively. From the upper reaches to the lower reaches, the habitat suitability of S. wangchiachii showed a longitudinal increasing trend. The proportion of the habitat quality below the good standard was 70%, while the proportion reaching the good and very good stan-dards was only 30%. The habitat of S. wangchiachii was mainly distributed in the natural flowing river sections with high hydrological connectivity of the river course, shallow water depth, abundant bait organisms and slow flow rate. The obvious spatial differences of its habitat suitability might be caused by human disturbances such as the construction of small dams.

Rhizosphere is the interface between roots and soils in forests, within which the micro-ecosystem is formed by the interaction of root metabolites, organisms and edaphic physicochemical factors. Due to root activities, rhizosphere has specific microbial community and function, with complex effects on forest growth and development and soil ecological processes. Development of high-throughput sequencing technology has advanced our understan-ding on the mechanism of rhizosphere microorganisms in plant growth promotion and stress resistance beyond the limitation of culture difficulties. Microbial community, function and interactions with forests were progressed well, but there are still gaps in the mechanism of rhizosphere microbial assembly regulated by plant metabolism and the development of synthetic microbial communities. We first summarized the functions of rhizosphere microorganisms in plant growth and stress resistance of forests, and addressed the application of synthetic microbial communities. Then, we discussed the effects of biotic and abiotic factors on rhizosphere microorganisms. Finally, we put forward the research on omics and community of forest rhizosphere microorganisms under the background of global climate changes, aiming to provide a theoretical support for the application of microbial resources in forest health maintenance and sustainable development of forestry.

Vegetation carbon sink research mostly focused on natural vegetation with large areas. A few studies analyzed carbon sinks of urban artificial greenspace, but few studies summarized the carbon sink function of urban wilderness, which is a research direction to explore the synergistic improvement of carbon sinks and biodiversity in urban ecosystems. With data from literature, we compared the carbon storage per unit area of urban wilderness and urban artificial greenspaces, from the aspects of vegetation and soil. We found that urban wilderness had a significant advantage over artificial greenspaces in terms of vegetation carbon storage per unit area. Among different types of urban wilderness, the carbon storage per unit area of woodlands/wetlands was significantly higher than that of abandoned or vacant brownfield areas and artificial greenspaces in industrial and commercial residential areas, but not significant against artificial greenspaces in park leisure area, from both vegetation and soil aspects. To increase urban carbon storage, we proposed measures to rewild artificial greenspaces and protect urban wilderness, especially woodlands/wetlands. Future research could explore the differences between urban wilderness and artificial green-spaces in terms of vegetation characteristics and soil properties, and examine the carbon storage of different plot types of urban wilderness.

Grazing exclusion is the most effective measure to restore the structure and function of degraded grasslands, and plays a crucial role in increasing ecosystem carbon (C) sequestration capacity. The dynamics and dri-ving mechanisms of soil organic carbon (SOC) after grazing exclusion have attracted great concerns, especially in the context of global change. By reviewing the current research on the SOC sequestration dynamics and its driving mechanisms after grazing exclusion, we aimed to clarify the SOC sequestration dynamics, explore the influencing mechanisms of plant C input and microbial community on SOC, analyze the driving mechanisms of photosynthetic C input and litter decomposition on SOC sequestration, and explore the contribution of plant and microbial necromass C to SOC sequestration after grazing exclusion. Long-term grazing exclusion improve the structure and function of soil microorganisms by increasing plant carbon inputs, and increase the content and proportion of soil stable organic C (such as mineral-associated organic C, plant and microbial necromass C, etc.), reducing mineralization efficiency of SOC and improving microbial C utilization efficiency, and consequently promoting SOC accumulation. In addition, SOC sequestration shows two trends of “first increasing and then stabilizing” and “first decreasing, following increasing and then stabilizing”, which are affected by the initial SOC level. Future studies should be strengthened in the SOC fraction dynamics, the C flow of SOC input, the decomposition process of SOC, and the microbial dri-ving mechanism after grazing exclusion.

Plant genome size, the sum of the DNA content of a complete set of haplo groups within a given plant species, is an important aspect of biological characterization. There is abundant genome size diversity in eukaryotes. Plant genome size is closely associated with a range of functional traits from the nucleus to individual level, exerts a vital role in shaping plant functional traits, and helps plants present different response strategies to environmental variables. We viewed the relationship between plant genome size and functional traits, such as cell size, stomatal size and density, photosynthetic functional traits, cell cycle, and seed mass. Their response and adaptation mechanisms to environmental variables, such as temperature, precipitation, altitude, nutrients, and heavy metal pollution, were discussed. Finally, the combination of genome size with functional traits and environmental adaptations was encouraged to deeply explore the response and adaptation mechanisms of plants to environmental changes in the context of global change.